Aging at Home: Integrating Community-Based Care for Older Persons
Bibliographic record
Abstract
Integrating community-based health and social care has grabbed international attention as a way of addressing the needs of aging populations while contributing to health systems' sustainability. However, integrating initiatives in different jurisdictions work (or do not work) within very various institutional and structural dynamics. The question is, what transferable lessons can we learn to guide policy makers and policy innovators at the local level? In this paper, we consider "aging at home" as a policy option in Ontario, and beyond. In the first section, we focus on the problem, in effect, what not to do. Here, we briefly review findings from national and international research literature and from our own research in Ontario that identify the costs and consequences of non-systems of care for older persons. In the second part, we turn to solutions, in effect, what to do. Drawing on our recent scoping review of the international literature, we identify three guiding principles, as well as a number of recommendations, for integrating care for older persons, knowing that important details of how to put such initiatives "on the ground" will be provided by other contributors to this journal edition.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".